Method and apparatus for bridge collision alert monitoring and impact analysis

Abstract

This is a method and apparatus for bridge collision alert and monitoring impact analysis, which allows users of the method and apparatus to continuously monitor the integrity of a bridge as well as to detect insult or impact to the bridge structure or both as well as viewing purposes as for forensic purposes. The system is comprised of a series of monitors that gather different pieces of date and integrate that data into a system for view by the operator.

1. A method and apparatus for bridge collision alert monitoring and impact analysis, which is comprised of:
 a. hardware; 
 wherein hardware to operate the system is provided; 
 wherein the hardware is comprised of a plurality of sensors; 
 wherein the hardware is comprised of a means of data acquisition; 
 said hardware is of a predetermined type; 
 b. sensors; 
 wherein a plurality of sensors gather information related to a collision with a bridge; 
 c. software; 
 wherein software is integrated with the hardware; 
 wherein said information is collected by the hardware and transmitted to the software; 
 wherein the software is comprised of a plurality of modules; 
 said software has certain features; 
 d. a plurality of modules; 
 wherein the modules gather data related to a collision alert monitoring impact analysis system; 
 said modules are interfaced within the software; 
 e. multi-sensory data acquisition module; 
 wherein the multisensory data acquisition module receives information from the data acquisition hardware; 
 wherein this module interfaces with the hardware and controls the interfaces with the hardware to control the interaction of events and extracts data; 
 f. sensory data logging module; 
 wherein a sensory data logging module is provided; 
 wherein the data is logged in a plurality of ways; 
 wherein the data is viewed in a plurality of ways; 
 g. sensory data analysis module; 
 wherein the sensory data analysis module is provided; 
 wherein the sensory data analysis module detects anomalies in the system; 
 h. a training module; 
 wherein a training module is provided; 
 wherein certain preset information is provided in the training module; 
 i. a classification module; 
 wherein a classification module is provided; 
 said classification module is equipped with a training classifier; 
 wherein the training classifier is used online; 
 j. an alarm management module; 
 wherein the alarm management module manages the alarms produced by different events; 
 k. a video acquisition module; 
 wherein a video acquisition module is provided; 
 wherein the video acquisition module permits video capability of events; 
 l. a data viewer; 
 wherein a data viewer synchronizes the video data, 
 sensory data, and alarm events; 
 wherein the events are displayed on the data viewer; 
 wherein a browsing capability for the data viewer is provided; 
 wherein a feature extraction capability is provided. 
 
     
     
       2. The method and apparatus as described in  claim 1  wherein the information from the database. 
     
     
       3. The method and apparatus as described in  claim 1  wherein the information from the sensor data logging module is stored in an XML format. 
     
     
       4. The method and apparatus as described in  claim 1  wherein the information from the sensor data logging module is stored in a file format. 
     
     
       5. The method and apparatus as described in  claim 1  wherein the data is viewed in a Web interface. 
     
     
       6. The method and apparatus as described in  claim 1  wherein the data is viewed in a Rich Client interface. 
     
     
       7. The method and apparatus as described in  claim 1  wherein the feature extraction capability is accomplished through domain analysis. 
     
     
       8. The method and apparatus as described in  claim 1  wherein the feature extraction analysis. 
     
     
       9. The method and apparatus as described in  claim 1  wherein the information from the training classifier is used with Support Vector Machines. 
     
     
       10. The method and apparatus as described in  claim 1  wherein the information from the training classifier is used with Neural Networks. 
     
     
       11. The method and apparatus as described in  claim 1  wherein the sensors are comprised of a plurality of cameras. 
     
     
       12. The method and apparatus as described in  claim 1  wherein the sensors are comprised of a plurality of accelerometers.